Severity of COVID-19 reinfection and associated risk factors: findings of a cross-sectional study in Bangladesh

  1. Md. Ziaul Islam
  2. Baizid Khoorshid Riaz
  3. Shah Ali Akbar Ashrafi
  4. Sharmin Farjana
  5. Syeda Sumaiya Efa
  6. Mohammad Adnan Khan

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Abstract

Background

COVID-19 reinfected patients suffer from diverse health consequences. Information on the severity of COVID-19 reinfection is scarce. The current study aimed to determine the proportion of COVID-19 reinfection and risk factors associated with its severity.

Methods

This cross-sectional study targeted all COVID-19 patients reported in May 2021 at the Health Information Unit (HIU) of the Directorate General of Health Services (DGHS) of Bangladesh. We identified 473 (1.14%) reinfected patients out of 41408 diagnosed cases by reviewing their medical records. Considering the selection criteria and informed consent, we enrolled 404 reinfected patients. Data were collected through telephone interviews and reviewing medical records using a semi-structured questionnaire and a checklist.

Results

The majority of the reinfected patients were urban residents (98.0%). Around 13.0% of reinfected patients had <90% oxygen saturation, and 64.0% had an interval of 3-6 months between two attacks. The severity of reinfection included asymptomatic (12.9%), mild (8.9%), moderate (66.3%), and severe (11.9%) forms of infection. An interval of 3-6 months between two attacks had less chance of having mild (AOR=0.031, ρ=0.000), moderate (AOR=0.132, ρ=0.017), and severe (AOR=0.059, ρ=0.002) infections. Patients who maintained physical distance had less chance of moderate-intensity reinfection (AOR=0.137, ρ=0.013), while the vaccinated patients had a higher chance of moderate (AOR=16.127, ρ=0.001) and severe (AOR=3.894, ρ=0.047) intensity reinfection.

Conclusion

To avert COVID-19 reinfection and its severity, patients should be vigilant about preventive practices even after recovery. The study suggests vibrant interventions aligned with exposure, physical distancing, vaccination, and comorbidities for mitigating reinfection.

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  1. ScreenIT

    SciScore for 10.1101/2021.12.26.21268408: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsIRB: The ethical approval was obtained from the Institutional Review Board (IRB) of the National Institute of Preventive and Social Medicine (NIPSOM), Dhaka, Bangladesh.
    Consent: Keeping compliance with Helsinki Declaration for medical research involving human subjects, we obtained informed verbal consent from each participant and recorded it in a digital recorder with the permission of the respective participant.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All collected data were compiled together using the Statistical Package for the Social Science (SPSS) software (Version 25.0, IBM Statistical Product and Service Solutions, Armonk, NY, USA).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Despite the limitation of telephone interview, our study findings provide new insight on the proportion of COVID-19 reinfection along with its severity and associated risk factors. The study also portrays information on the association of the severity of reinfection with preventive practices and the vaccination status of patients. The study findings could contribute to designing an efficient preventive algorithm to alleviate COVID-19 reinfection in a more pragmatic approach. The study conserves decisive policy implications for devising effective interventions to prevent the severity of COVID-19 reinfection. Moreover, the study inspires future inclusive studies on the COVID-19 reinfection and offers a scope of comparison considering geographical, demographical, socio-cultural, epidemiological, and clinical determinants.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2021.12.26.21268408v1 on medRxiv